scholarly journals Impact of the measurement uncertainty on the monitoring of thermal comfort through AI predictive algorithms

ACTA IMEKO ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 221
Author(s):  
Nicole Morresi ◽  
Sara Casaccia ◽  
Marco Arnesano ◽  
Gian Marco Revel
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Relative Humidity ◽  
Measurement Uncertainty ◽  
Thermal Comfort ◽  
Air Temperature ◽  
Air Velocity ◽  
Human Thermal Comfort ◽  
Innovative Method ◽  
Predictive Algorithms

This paper presents an approach to assess the measurement uncertainty of human thermal comfort by using an innovative method that comprises a heterogeneous set of data, made by physiological and environmental quantities, and artificial intelligence algorithms, using Monte Carlo method (MCM). The dataset is made up of heart rate variability (HRV) features, air temperature, air velocity and relative humidity. Firstly, MCM is applied to compute the measurement uncertainty of the HRV features: results have shown that among 13 participants, there are uncertainty values in the measurement of HRV features that ranges from ±0.01% to ±0.7 %, suggesting that the uncertainty can be generalized among different subjects. Secondly, MCM is applied by perturbing the input parameters of random forest (RF) and convolutional neural network (CNN) algorithm, trained to measure human thermal comfort. Results show that environmental quantities produce different uncertainty on the thermal comfort: RF has the highest uncertainty due to the air temperature (14 %), while CNN has the highest uncertainty when relative humidity is perturbed (10.5 %). A sensitivity analysis also shows that air velocity is the parameter that causes a higher deviation of thermal comfort

scholarly journals Human Thermal Comfort Situation in the Goller (Lakes) District of Turkey

2016 ◽  
pp. 137-144
Author(s):  
Yuksel Guclu
Keyword(s):  
Relative Humidity ◽  
Thermal Comfort ◽  
Human Health ◽  
Air Temperature ◽  
Mediterranean Region ◽  
Human Thermal Comfort ◽  
Almost All ◽  
Relative Humidity Data ◽  
Recreation Activities

Abstract In this study, the determination of the human thermal comfort situation in the Goller District (in the Mediterranean Region) of Turkey has been aimed. In the direction of the aim, the air temperature and relative humidity data of total 11 meteorology stations have been examined according to The Thermo-hygrometric Index (THI) and the New Summer Simmer Index (SSI). According to this, it has been determined that the thermal comfort conditions are not appropriate in the period of October-May on average monthly. The months of June and September are the most appropriate to almost all kinds of tourism and recreation activities in the outdoor in terms of thermal comfort. When THI and SSI indices’ values are evaluated together, the periods between 5th – 25th June and 29th August-16th September are the most appropriate periods in the study area on average in terms of the thermal comfort for the tourism and recreation activities in the outdoor. Keywords: Thermal comfort, human health, The Thermo-Hygrometric Index, The Summer Simmer Index, Goller District, Turkey.

Thermal comfort analysis of radiant cooling panels with dedicated fresh-air system

2020 ◽  
pp. 1420326X2096114
Author(s):  
S. Y. Qin ◽  
X. Cui ◽  
C. Yang ◽  
L. W. Jin
Keyword(s):  
Relative Humidity ◽  
Surface Temperature ◽  
Thermal Comfort ◽  
Air Temperature ◽  
Indoor Air ◽  
Area Ratio ◽  
Human Thermal Comfort ◽  
Air Supply ◽  
Radiant Cooling ◽  
Air System

Radiant system has been increasingly applied in buildings due to its good thermal comfort and energy-saving potential. In this research, a simplified predicted mean vote (PMV) model and sensible cooling load equation were proposed based on human thermal comfort. Simulations were carried out using Airpak to explore relationships among thermal comfort characteristics, design and operation parameters. Results show that radiant surface temperature, fresh-air supply temperature and the area ratio are correlated approximately linearly with the indoor air temperature, while the relative humidity has little effect on the indoor air temperature. The indoor air velocity in the simulated environment was no more than 0.15 m/s, satisfying the requirements of limit values in the occupied zone. The results indicate that the optimum radiant surface temperature ( tc) is 19°C to 23°C when fresh-air supply temperature ( ts) is 26°C. The relative humidity ( φ) should be maintained at 50% to 70%, and the area ratio of radiant panels to total surfaces ( k1) should be kept within 0.15 to 0.38 when the radiant surface temperature is 20°C and the fresh-air supply temperature is 26°C. The simplified PMV model and the sensible load equation can provide reference for panel design based on characteristics of radiant cooling panels with a dedicated fresh-air system.

Modeling of Basil Leaves Drying by GA–ANN

2013 ◽  
Vol 9 (4) ◽  
pp. 393-401 ◽  
Author(s):  
Amin Taheri-Garavand ◽  
Shahin Rafiee ◽  
Alireza Keyhani ◽  
Payam Javadikia
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Relative Humidity ◽  
Moisture Content ◽  
Air Temperature ◽  
High Accuracy ◽  
Air Velocity ◽  
Feed Forward Neural Network ◽  
Air Temperatures ◽  
Hidden Layer

AbstractIn this research, the experiment is done by a dryer. It could provide any desired drying air temperature between 20 and 120°C and air relative humidity between 5 and 95% and air velocity between 0.1 and 5.0 m/s with high accuracy, and the drying experiment was conducted at five air temperatures of 40, 50, 60, 70 and 80°C and at three relative humidity 20, 40 and 60% and air velocity of 1.5, 2 and 2.5 m/s to dry Basil leaves. Then with developed Program in MATLAB software and by Genetic Algorithm could find the best Feed-Forward Neural Network (FFNN) structure to model the moisture content of dried Basil in each condition; anyway the result of best network by GA had only one hidden layer with 11 neurons. This network could predict moisture content of dried basil leaves with correlation coefficient of 0.99.

The Study of Thermal Comfort and Noise Level in Battery Plate Factory

2014 ◽  
Vol 663 ◽  
pp. 474-479
Author(s):  
Mohd Anas Mohd Sabri ◽  
Mohd Faizal Mat Tahir ◽  
Kamaruzaman Sopian ◽  
Muhammad Hadi Zabidi Rosdi
Keyword(s):  
Relative Humidity ◽  
Metabolic Rate ◽  
Thermal Comfort ◽  
Air Temperature ◽  
Noise Level ◽  
Comfort Level ◽  
The Other ◽  
Air Velocity ◽  
Other Hand ◽  
Radiant Temperature

The successful of manufacturing factories in industry is highly dependent on a productivity of their employees especially operators. It was identified that comfort and noise level can reduce the productivity of their workers. This study is to determine the level of thermal and noise comfort in the battery plate factory. This study was conducted in three days and location of the study is at battery plate factory in Semenyih, Selangor, Malaysia. The scope of study is focused at plate manufacturing area where the employee estimated 40 persons. The thermal comfort level can be determined by calculating PMV and PPD. This study involved six factors of comfort which is air temperature, average radiant temperature, air velocity, relative humidity, metabolic rate and clothes insulation. Then the study of noise level was conducted by determining LAeq, T, Lmax and Lmin. To carry out this study, Babuc-A equipment were used. The analysis show the area of the manufacturing battery plate having a discomfort condition and PMV result is between 1.5 until 3. Air temperature on the other hand is between 27.4°C-37.8°C while relative humidity is between range 35.35% -92.1% and air velocity 0 m/s-1.28 m/s. Meanwhile the LAeq,T value in the factory is varied from 68 to 80 dB.

scholarly journals Artificial Neural Network for the Thermal Comfort Index Prediction: Development of a New Simplified Algorithm

Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4500
Author(s):  
Domenico Palladino ◽  
Iole Nardi ◽  
Cinzia Buratti
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Relative Humidity ◽  
Thermal Comfort ◽  
Air Temperature ◽  
Thermal Conditions ◽  
Feed Forward Neural Network ◽  
Clothing Insulation ◽  
Artificial Neural ◽  
Simplified Algorithm

A simplified algorithm using an artificial neural network (ANN, a feed-forward neural network) for the assessment of the predicted mean vote (PMV) index in summertime was developed, using solely three input variables (namely the indoor air temperature, relative humidity, and clothing insulation), whilst low air speed (<0.1 m/s), a minimal variation of radiant temperature (25.1 °C ± 2 °C) and steady metabolism (1.2 Met) were considered. Sensitivity analysis to the number of variables and to the number of neurons were performed. The developed ANN was then compared with three proven methods used for thermal comfort prediction: (i) the International Standard; (ii) the Rohles model; (iii) the modified Rohles model. Finally, another network able to predict the indoor thermal conditions was considered: the combined calculation of the two networks was tested for the PMV prediction. The proposed algorithm allows one to better approximate the PMV index than the other models (mean error of ANN predominantly in ±0.10–±0.20 range). The accuracy of the network in PMV prediction increases when air temperature and relative humidity values fall into 21–28 °C and 30–75% ranges. When the PMV is predicted by using the combined calculation (i.e., by using the two networks), the same order of magnitude of error was found, confirming the reliability of the networks. The developed ANN could be considered as an alternative method for the simplified prediction of PMV; moreover, the new simplified algorithm can be useful in buildings’ design phase, i.e., in those cases where experimental data are not available.

Design Range of Indoor Relative Humidity in Radiant Cooling Environment

2011 ◽  
Vol 243-249 ◽  
pp. 4905-4908
Author(s):  
Xue Min Sui ◽  
Xu Zhang ◽  
Guang Hui Han
Keyword(s):  
Relative Humidity ◽  
Thermal Comfort ◽  
Mean Radiant Temperature ◽  
Design Standards ◽  
Human Thermal Comfort ◽  
Radiant Cooling ◽  
Climate Parameter ◽  
Radiant Temperature ◽  
Thermal Comfort Model ◽  
The Impact

Relative humidity is an important micro-climate parameter in radiant cooling environment. Based on the human thermal comfort model, this paper studied the effect on PMV index of relative humidity, and studied the relationship of low mean radiant temperature and relative humidity, drew the appropriate design range of indoor relative humidity for radiant cooling systems.The results show that high relative humidity can compensate for the impact on thermal comfort of low mean radiant temperature, on the premise of achieving the same thermal comfort requirements. However, because of the limited compensation range of relative humidity, together with the constraints for it due to anti-condensation of radiant terminal devices, the design range of relative humidity should not be improved, and it can still use the traditional air-conditioning design standards.

Thermal Lethality of Salmonella in Chicken Leg Quarters Processed via an Air/Steam Impingement Oven

2004 ◽  
Vol 67 (3) ◽  
pp. 493-498 ◽  
Author(s):  
R. Y. MURPHY ◽  
K. H. DRISCOLL ◽  
L. K. DUNCAN ◽  
T. OSAILI ◽  
J. A. MARCY
Keyword(s):  
Relative Humidity ◽  
Surface Area ◽  
Air Temperature ◽  
Cooking Time ◽  
Air Velocity ◽  
Poultry Products ◽  
Product Surface ◽  
Cooking Times

Chicken leg quarters were injected with 0.1 ml of the cocktail culture per cm2 of the product surface area to contain about 7 log(CFU/g) of Salmonella. The inoculated leg quarters were processed in an air/steam impingement oven at an air temperature of 232°C, an air velocity of 1.4 m/s, and a relative humidity of 43%. The endpoint product temperatures were correlated with the cooking times. A model was developed for pathogen thermal lethality up to 7 log(CFU/g) reductions of Salmonella in correlation to the product mass (140 to 540 g) and cooking time (5 to 35 min). The results from this study are useful for validating thermal lethality of pathogens in poultry products that are cooked via impingement ovens.

scholarly journals A Study on Suitable Habitat for Swiftlet Farming

2009 ◽  
Vol 1 (1) ◽  
pp. 1-7
Author(s):  
Ibrahim S. H. ◽  
Teo W.C. ◽  
Baharun A.
Keyword(s):  
Relative Humidity ◽  
Light Intensity ◽  
Air Temperature ◽  
Capital Investment ◽  
Suitable Habitat ◽  
Key Factors ◽  
Air Velocity ◽  
Animal Products ◽  
New Industry ◽  
Temperature Surface

Swiftlet farming is a new industry in Sarawak as compared to other long-standing industries such as rubber, palm oil and timber. It is one of the businesses that involved a small capital investment that could generate enormous returns in the future. Swiftlet farming involves the conversion of human-centric building into structures for Swiftlet. The purpose of this conversion is to let Swiftlet for nesting and protect them. The design and construction of such building will also helps to accommodate Swiftlets' population. The nest of the Edible-nest Swiftlet rank amongst the world's most expensive animal products. Therefore, in order to increase the productivity of bird nest, study of the suitable habitat for Swiftlet should be done thoroughly. Environmental factors such as air temperature, surface temperature, relative humidity, air velocity and light intensity are the key factors for a successful Swiftlet farm house. Internal air temperature of building should be maintained from 26°C to 35°C, relative humidity from 80% to 90%, low air velocity and light intensity less than 5 LUX. Proper ventilation and installation of a humidifier could help the building to achieve the desirable range of environment factors. Location of structure will also be considered from direct sunlight direction to reduce the internal temperature. Only licensed Swiftlet farming is legal.

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